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ISSN: 232 7782 (Online) 1
Computer Science and Management Studies
International Journal of Advance Research in Volume 2, Issue 12, December 2014
Research Article / Survey Paper / Case Study Available online at: www.ijarcsms.com
New Steganography approach using encrypted secret message inside Audio and Video media
Pritha Roy1 Department of Computer Science
St. Xavier’s College(Autonomous) Kolkata, India
Dr. Asoke Nath2 Department of Computer Science
St. Xavier’s College(Autonomous) Kolkata, India
Abstract: Steganography is the technique of hiding any secret information like password, data and image behind any cover
file. The word steganography comes from the Greek Steganos, which means covered or secret and -graphy means writing or
drawing. Therefore, steganography means, literally, covered writing. In paper proposes a method which is an audio-video
crypto steganography system which is the combination of audio steganography and video steganography using advanced
chaotic algorithm as the secure encryption method. The aim is to hide secret information behind image and audio of video
file. Since video is the application of many audio and video frames, we can select a particular frame for image hiding and
audio for hiding our secret data.4LSB substitution can be used for image steganography and LSB substitution algorithm
with location selection for audio steganography. Suitable parameter of security and authentication such as PSNR value,
histograms are obtained at both the receiver side and transmitter sides which are found to be identical at both ends.
Reversible data hiding methods for both video and audio are also being mentioned. Hence the security of the data and image
can be enhanced. This method can be used in fields such as medical and defence which requires real time processing. Here,
we propose a data hiding and extraction procedure for high resolution AVI (Audio Video Interleave) videos. Although AVI
videos are large in size but it can be transmitted from source to target over network after processing the source video by
using these Data Hiding and Extraction procedure securely. There are two different procedures, which are used here at the
sender’s end and receiver’s end respectively. The procedures are used here as the key of Data Hiding and Extraction.
Keywords: Steganography, Audio Steganography, Video Steganography, AVI, LSB
I. INTRODUCTION
The objective of steganography is to hide a secret message within a cover-media in such a way that others cannot discern
the presence of the hidden message. Modern steganography uses the opportunity of hiding information into digital multimedia
files and also at the network packet level. Hiding information into a media requires following elements [2] :
1. The cover media(C) that will hold the hidden data
2. The secret message (M), may be plain text, cipher text or any type of data
3. The stego function (Fe) and its inverse (Fe-1)
4. An optional stego-key (K) or password may be used to hide and unhide the message.
The stego function operates over cover media and the message (to be hidden) along with a stego-key (optionally) to
produce a stego media (S). The schematic of steganographic operation is shown below.
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Fig 1: The Steganographic operation
Steganography and Cryptography are great partners in spite of functional difference. It is common practice to use
cryptography with steganography. The steganography is the art of hiding data inside another data such as cover medium by
applying different steganographic techniques. While cryptography results in making the data human unreadable form called as
cipher thus cryptography is scrambling of messages. Whereas the steganography results in exploitation of human awareness so
it remains unobserved and undetected or intact. It is possible to use all file medium, digital data, or files as a cover medium in
steganography. Generally steganography technique is applied where the cryptography is ineffective.
Modern techniques of steganography
The common modern technique of steganography exploits the property of the media itself to convey a message. The
following media are the candidate for digitally embedding message: -
» Plaintext
» Still imagery
» Audio and Video
» IP datagram
a) Audio Steganography
The basic model of Audio steganography consists of Carrier (Audio file), Message and Password. Carrier is also known as
a cover-file, which conceals the secret information. Basically, the model for steganography is shown in Fig 2. Message is the
data that the sender wishes to remain it confidential. Message can be plain text, image, audio or any type of file. Password is
known as a stego-key, which ensures that only the recipient who knows the corresponding decoding key will be able to extract
the message from a cover-file. The cover-file with the secret information is known as a stego-file.
The information hiding process consists of following two steps.
» Identification of redundant bits in a cover-file. Redundant bits are those bits that can be modified without corrupting
the quality or destroying the integrity of the cover-file.
» To embed the secret information in the cover file, the redundant bits in the cover file is replaced by the bits of the
secret information.
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In audio steganography, secret message is embedded into digitized audio signal which result slight altering of binary
sequence of the corresponding audio file. There are several methods are available for audio steganography. Some of them are as
follows:
1) LSB CODING: Sampling technique followed by Quantization converts analog audio signal to digital binary sequence.
Fig 3: Sampling of the Sine Wave followed by Quantization process.
In this technique LSB of binary sequence of each sample of digitized audio file is replaced with binary equivalent of secret
message. For example if we want to hide the letter ‘A’ (binary equivalent 01100101) to an digitized audio file where each
sample is represented with 16 bits, then LSB of 8 consecutive samples (each of 16 bit size) is replaced with each bit of binary
equivalent of the letter ‘A’.
Sampled Audio Stream (16 bit) ‘A’ in binary Audio stream with encoded message 1001 1000 0011 1100 0 1001 1000 0011 1100 1101 1011 0011 1000 1 1101 1011 0011 1001 1011 1100 0011 1101 1 1011 1100 0011 1101 1011 1111 0011 1100 0 1011 1111 0011 1100 1011 1010 0111 1111 0 1011 1010 0111 1110 1111 1000 0011 1100 1 1111 1000 0011 1101 1101 1100 0111 1000 0 1101 1100 0111 1000 1000 1000 0001 1111 1 1000 1000 0001 1111
2) PARITY CODING:
Parity coding is one of the robust audio steganographic technique. Instead of breaking a signal into individual samples, this
method breaks a signal into separate samples and embeds each bit of the secret message from a parity bit. If the parity bit of a
selected region does not match the secret bit to be encoded, the process inverts the LSB of one of the samples in the region.
Thus, the sender has more of a choice in encoding the secret bit. Figure 4, shows the parity coding procedure.
Fig 4. Parity coding
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3) PHASE CODING:
The phase coding technique works by replacing the phase of an initial audio segment with a reference phase that represents
the secret information. The remaining segments phase is adjusted in order to preserve the relative phase between segments. In
terms of signal to noise ratio, Phase coding is one of the most effective coding methods. When there is a drastic change in the
phase relation between each frequency component, noticeable phase dispersion will occur. However, as long as the modification
of the phase is sufficiently small, an inaudible coding can be achieved . This method relies on the fact that the phase
components of sound are not as per the human ear as noise is. Phase coding is explained in the following procedure:
1. Divide an original sound signal into smaller segments such that lengths are of the same size as the size of the message
to be encoded.
2. Matrix of the phases is created by applying Discrete Fourier Transform (DFT).
3. Calculate the Phase differences between adjacent segments.
4. Phase shifts between adjacent segments are easily detectable. It means, we can change the absolute phases of the
segments but the relative phase differences between adjacent segments must be preserved. So the secret information is
inserted only in the phase vector of the first signal segment as follows:
5. Using the new phase of the first segment a new phase matrix is created and the original phase differences.
6. The sound signal is reconstructed by applying the inverse Discrete Fourier Transform using the new phase matrix and
original magnitude matrix and then concatenating the sound segments back together.
The receiver must know the segment length to extract the secret information from the sound file. Then the receiver can use
the DFT to get the phases and extract the secret information .
Fig 5. Phase coding
4) SPREAD SPECTRUM:
In audio steganography, the basic spread spectrum (SS) method attempts to spread secret information across the frequency
spectrum of the audio signal. This is similar to a system which uses an implementation of the LSB that spreads the message bits
randomly over the entire sound file. However, unlike LSB coding, the Spread Spectrum method spreads the secret information
over the frequency spectrum of the sound file using a code which is independent of the actual signal . As a result, the final
signal occupies a bandwidth which is more than what is actually required for transmission. The Spread Spectrum method is
capable of contributing a better performance in some areas compared to LSB coding, phase coding, and parity coding
techniques in that it offers a moderate data transmission rate and high level of robustness against removal techniques. However,
the Spread Spectrum method has one main disadvantage that it can introduce noise into a sound file. The Spread Spectrum steps
are shown in Figure 6.
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Fig 6. Spread Spectrum (SS)
5) ECHO HIDING:
Echo hiding technique embeds secret information in a sound file by introducing an echo into the discrete signal. Echo
hiding has advantages of providing a high data transmission rate and superior robustness when compared to other methods.
Only one bit of secret information could be encoded if only one echo was produced from the original signal. Hence, before the
encoding process begins the original signal is broken down into blocks. Once the encoding process is done, the blocks are
concatenated back together to create the final signal [5, 20]. Echo Hiding is shown in Figure 7.
Fig 7. Echo hiding
b) Video Steganography
Digital video is a very promising host candidate that can carry a large amount of data (payload) and its potential for secret
communications is largely unexplored. Since a video is formed from a sequence of frames, it presents the data hider with the
possibility to embed and send a large amount of data. The requirements of any data hiding system can be categorized into
security, capacity and robustness Cox et al. (1996). All these factors are inversely proportional to each other creating the so
called data hiding dilemma. The focus of this paper aims at maximizing the first two factors of data hiding i.e. security and
capacity coupled with alteration detection. The proposed scheme is a data-hiding method that uses high resolution digital video
as a cover signal. The proposed scheme provides the ability to hide a significant quality of information making it different from
typical data hiding mechanisms because here application that require significantly larger payloads like video-in-video and
picture-in-video is considered. Data hiding requirements include the following:
1. Imperceptibility- The video with data and original data source should be perceptually identical.
2. Robustness- The embedded data should survive any processing operation the host signal goes through and preserve its
fidelity.
3. Capacity-Maximize data embedding payload.
4. Security- Security is in the key.
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Data Hiding is the different concept than cryptography, but uses some of its basic principles .In this paper, some important
features of data hiding have been considered. The consideration is that of embedding information into video, which could
survive attacks on the network. Some important video Steganography methods are:
1) Least Significant Bit Modifications:
The most widely used technique to hide data, is the usage of the LSB. Although there are several disadvantages to this
approach, the relative easiness to implement it, makes it a popular method. To hide a secret message inside a image, a proper
cover image is needed. Because this method uses bits of each pixel in the image, it is necessary to use a lossless compression
format, otherwise the hidden information will get lost in the transformations of a lossy compression algorithm. When using a
24 bit color image, a bit of each of the red, green and blue color components can be used, so a total of 3 bits can be stored in
each pixel. Thus, a 800 ×600 pixel image can contain a total amount of 1.440.000 bits (180.000 bytes) of secret data. For
example, the following grid can be considered as 3 pixels of a 24 bit color image, using 9 bytes of memory:
(00100111 11101001 11001000)
(00100111 11001000 11101001)
(11001000 00100111 11101001)
When the character A, which binary value equals 10000001, is inserted, the following grid results:
(00100111 11101000 11001000)
(00100110 11001000 11101000)
(11001000 00100111 11101001)
In this case, only three bits needed to be changed to insert the character successfully. On average, only half of the bits in an
image will need to be modified to hide a secret message using the maximal cover size. The resulting changes that are made to
the least significant bits are too small to be recognized by the human eye, so the message is effectively hidden. While using a 24
bit image gives a relatively large amount of space to hide messages,it is also possible to use a 8 bit image as a cover source.
Because of the smaller space and different properties, 8 bit images require a more careful approach. Where 24 bit images use
three bytes to represent a pixel, an 8 bit image uses only one. Changing the LSB of that byte will result in a visible change of
color, as another color in the available palette will be displayed. Therefore, the cover image needs to be selected more carefully
and preferably be in grayscale, as the human eye will not detect the difference between different gray values as easy as with
different colors.
2) Masking And Filtering:
Masking and filtering techniques, usually restricted to 24 bits or grayscale images, take a different approach to hiding a
message. These methods are effectively similar to paper watermarks, creating markings in an image. This can be achieved for
example by modifying the luminance of parts of the image. While masking does change the visible Properties of an image, it
can be done in such a way that the human eye will not notice the anomalies.Since masking uses visible aspects of the image, it
is more robust than LSB modification with respect to compression, cropping and different kinds of image processing. The
information is not hidden at the ”noise” level but is inside the visible part of the image, which makes it more suitable than LSB
modifications in case a lossy compression algorithm like JPEG is being used .
3) Transformations:
A more complex way of hiding a secret inside an image comes with the use and modifications of discrete cosine
transformations. Discrete cosine transformations (DST)), are used by the JPEG compression algorithm to transform successive 8
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x 8 pixel blocks of the image, into 64 DCT coefficients each. Each DCT coefficient F(u, v) of an 8 x 8 block of image pixels
f(x, y) is given by:
Where Q(u, v) is a 64-element quantization table. A simple pseudo-code algorithm to hide a message inside a JPEG image
could look like this:
Input: Message, cover image
Output: steganographic image containing message
While data left to embed do
Get next DCT coefficient from cover image
If DCT not equal to 0 and DCT not equal to 1 then
Get next LSB from message
Replace DCT LSB with message bit
End if
Insert DCT into steganographic image
End while
Although a modification of a single DCT will affect all 64 image pixels, the LSB of the quantized DCT coefficient can be
used to hide information. Lossless compressed images will be suspect able to visual alterations when the LSB are modified.
This is not the case with the above described method, as it takes place in the frequency domain inside the image, instead of the
spatial domain and therefore there will be no visible changes to the cover image. When information is hidden inside video the
program or person hiding the information will usually use the DCT (Discrete Cosine Transform) method. DCT works by
altering values of certain parts of the images, it usually rounds them up. For example if part of an image has a value of 6.667 it
will round it up to 7. Data Hiding in Videos is similar to that of Data Hiding in Images, apart from information is hidden in each
frame of the video.
II. PROPOSED METHOD
a) For Audio Steganography
Here we will discuss the disadvantages of the previous procedure and how those are different with present method. The
main disadvantages associated with the use of existing methods like echo hiding, spread spectrum and parity coding are, human
ear is very sensitive to noise and it can often detect even the slightest bit of noise introduced into a sound file and another
problem is robustness. Phase coding has main disadvantage of low data transmission rate because of the fact that the secret
message is encoded only in the first signal segment. Hence this method is used only when a small amount of data needs to be
transferred. Among different information hiding techniques proposed to embed secret information within audio file, Least
Significant Bit (LSB) coding method is the simplest way to embed secret information in a digital audio file by replacing the
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least significant bit of audio file with a binary message. Hence LSB method allows large amount of secret information to be
encoded in an audio file. Figure 8 and figure 9 represents the complete working of the audio stegnography process of
embedding the encrypted secret message using public key cryptographic algorithm, RSA into the 4th and 5th layers of the audio
file. In the sender side, the text file which has to be embedded into an audio file is encrypted using public key cryptographic
algorithm, RSA. The cipher text obtained is then embedded in the 4th AND 5th LSB bit using one of the Steganographic
algorithms, LSB algorithm. The resultant audio file contains the secret message embedded into it. On the receiver side, the
embedded audio file is selected to extract the secret message. The secret message is decrypted using RSA decryption method
and the secret messages are compared before embedding and after embedding. Also, comparisons are made based on PSNR of
both original audio file and embedded audio file, to indicate that less noise intrusion even after changing the 4th and 5th LSB bit
of the original wave.
SENDER
Fig .8: Sender
Fig.9: Receiver
Algorithm For Embedding Text File Content Into Audio File At The Sender Side.
Step1: Select the audio file for embedding the secret message.
Step2: Play the audio file so that it sounds clear to the end user.
Step3: Select the text file containing the secret message.
Step4: Encrypt the text file contents.
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Step5: Compare text file and audio file size. If text file size > audio file contents Error message displayed indicating
cannot embed secret message.
Else
Embed secret message in the audio file in the 4th and 5th LSB bit of every sample.
Step6: Display message to user of the new audio file created after embedding secret message.
Algorithm For Extracting The Embedded Text From Audio File At The Receiver Side.
Step 1: Select the new audio file for extracting the secret message.
Step 2: Extract the secret message from the audio file from the 4th and 5th LSB bit of every sample.
Step 3: If secret message present in audio file Then
Display message to end user after extracting message.
Else
Display that no hidden data is present in the text.
Step 4: Decrypt the secret message.
Step 5: Display message to end user after decrypting the message.
b) For Video Steganography
The main high resolution AVI fie is nothing but a sequence of high resolution image called frames. Initially stream the
video and collect all the frames in bitmap format (Figure 1). And also collect the following information:
1. Starting frame: It indicates the frame from which the algorithm starts message embedding.
2. Starting macro block: It indicates the macro block within the chosen frame from which the algorithm starts message
embedding.
3. Number of macro blocks: It indicates how many macro blocks within a frame are going to be used for data hiding.
These macro blocks may be consecutive frame according to a predefined pattern. Apparently, the more the macro
blocks we use, the higher the embedding capacity we get. Moreover, if the size of the message is fixed, this number
will be fixed, too. Otherwise it can be dynamically changed.
4. Frame period: It indicates the number of the inter frames, which must pass, before the algorithm repeats the
embedding. However, if the frame period is too small and the algorithm repeats the message very often, that might
have an impact onto the coding efficiency of the encoder. Apparently, if the video sequence is large enough, the frame
period can be accordingly large. The encoder reads these parameters from a file. The same file is read by the software
that extracts the message, so as both of the two codes to be synchronized. After streaming the AVI video file into AVI
frames the conventional LSB replacement method is used. Recently it has been claimed that LSB replacement
involving more than one least significant bit planes is less detectable than single bit plane LSB replacement. Hence the
use of multiple bit planes for embedding has been encouraged. But the direct use of 3 or more bit planes leads to
addition of considerable amount of noise in the cover image. Still as the work is in high resolution video so get a RGB
combination of each pixel as in Figure 2 hence if one LSB is considered there is a choice of 3 bits for each pixel. This
will give a higher security of the Data Hiding method.
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Fig1. AVI video Streaming and Data Hiding Algorithm
Fig2. The RGB bit Pattern
III. RESULTS AND DISCUSSION
a) For Audio Steganography
Different experiments were conducted to prove that the proposed method of embedding audio file. The following
experiments were conducted by modifying the 4th and 5th bit LSB with same data and different data.
1. Same audio file is embedded with different text file with varying text content sizes.
2. Different audio files of different time durations are taken and embedded with same text content.
3. Different categories of audio file are considered and embedded with same text content.
In all the cases, SNR (Signal to Noise Ratio) and PSNR (Peak; Signal to Noise Ratio) area calculated. Figure 10 shows the
original audio file before embedding the text content and Figure 11 shows the audio file after embedding the text content. The
results show that the size of the audio file remains same even after embedding the secret message.
Fig. 10 .Original audio file Fig. 11 .Embedded audio file
The results of the experiment conducted by changing the 4th and 5th LSB bit with same data have been tabulated in Table
I, Table II and Table III.
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Table I . SNR/PSNR Values For Same Audio File With Varying Text Content Sizes
Table II .SNR/PSNR Values For Different Audio Files Of Different Time Durations With Same Text Content
Table III . SNR/PSNR Values For Different Categories Of Audio File With Same Text Content
The results of the experiment conducted by changing the 4th and 5th LSB bit with different data have been tabulated in
Table IV, Table V and Table VI.
Table IV . SNR/PSNR Values For Same Audio File With Varying Text Content Sizes
Table V. SNR/PSNR Values For Different Audio Files Of Different Time Durations With Same Text Content
Audio File Duration : 60 sec
File Name Size(Bytes) SNR PSNR
Text 1 103 -2.22E-08 16.66214531
Text 2 100 -2.19E-08 16.66214531
Text 3 75 -2.17E-08 16.66214531
Text 4 50 -2.17E-08 16.66214531
Text 5 25 -2.24E-08 16.66214531
Text File size : 103 Bytes File Name Duration(sec) SNR PSNR Sample_15 15 -1.25E-07 17.50264063 Sample_30 30 -4.83E-08 17.16767049 Sample_60 60 -2.19E-08 16.66214531 Sample_80 80 -1.65E-08 16.6129556 Sample_90 90 -1.47E-08 16.61077829 Sample_100 100 -1.30E-08 16.63435136
Audio File Duration : 60sec File Name Size(Bytes) SNR PSNR HARDCORE 103 2.58E-06 11.2635686 HIPHOP 103 2.02E-06 10.98351 JAZZ 103 -9.66E-09 17.719165 METAL 103 -2.52E-08 10.6906624 POP 103 -3.38E-08 10.4659678 ROCK 103 -6.97E-08 13.5509855
Audio File Duration : 60 sec File Name Size(Bytes) SNR PSNR Text 1 103 -6.84E-09 16.662145312 Text 2 100 -6.80E-09 16.662145312 Text 3 75 -6.88E-09 16.662145312 Text 4 50 -6.85E-09 16.662145312 Text 5 25 -6.84E-09 16.662145312
Text File size : 103 Bytes File Name Duration(sec) SNR PSNR Sample_15 15 -3.77E-08 17.50264072 Sample_30 30 -1.51E-08 17.16767052 Sample_60 60 -6.78E-09 16.66214532 Sample_80 80 -5.12E-09 16.61295561
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Table VI . SNR/PSNR Values For Different Categories Of Audio File With Same Text Content
By these details we can see that the SNR and PSNR values reduce as the file size increases, indicating that weak noise is
not harmful to the changed bits at higher layers.
b) For Video Steganography
Data size estimation: Each frame of the Video is taken a data source for Data Hiding. First the maximum size of the hiding
data is calculated as shown in Figure 3. The size of the image is 2000 × 1000 and modified it to 2048 × 1024. On further
calculations we get 786,432,000 chars that can be embedded. The following equation mentioned below have been followed:
(((Width × height) × 3 bits)/8 bits)/3 bytes × 3000 frames = char/video
And the image Bitmap size = 2048 × 1024
Step of calculations the maximum of hiding information:
1. Each frame consist = 2048 × 1024 = 2, 097, 152 Pixels.
2. Each pixel include 3 bytes (One byte we use single bit for encode data hiding) R = 1 bit, G = 1 bit and B = 1 bit.
3. Each frame = Pixels ×3 = 2, 097, 152 × 3 = 62, 915, 456 bits.
4. Each frame we can maximum hiding data is 62, 915, 456 bits/8 bits = 786, 432 bytes.
5. If this video 3000 frames = 786, 432 × 3000 = 2, 359.296, 000 bytes (1 bytes = 1Character).
6. For 1 Character of Unicode we need 3 bytes/1 character of Unicode = 2, 359.296,000 bytes/3 =786, 432, 000 chars.
Fig 3
IV. AUTHENTICATION
Authentication is mainly done to confirm the real identity of the data or image or whatever entities. It is mainly done to
ensure that it came from the real user. Here authentication is mainly done for the security purpose at both the transmitter as well
as the receiver for secure communication. The data hiding key provided at the transmitter side act as the authentication key in
audio steganography. In case of video hiding the frame number and the triple key provided as the encryption key acts as the tool
for authentication. The strength of the key used decides the strength of authentication.
Sample_90 90 -4.47E-09 16.6107783 Sample_100 100 -4.03E-09 16.66E+01
Audio File Duration : 60sec File Name Size(Bytes) SNR PSNR HARDCORE 103 1.52E-06 11.2635751 HIPHOP 103 1.29E-06 10.98350927 JAZZ 103 4.06E-09 17.71916498 METAL 103 -7.81E-09 10.69066241 POP 103 -1.01E-08 10.46596782 ROCK 103 -2.15E-08 13.55098551
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V. CONCLUSION
The proposed systems are considered to be an efficient method for hiding message in audio and video files such that data
can reach the destination in a safe manner without being modified. Using the method of embedding text in the 4th and 5th layer
with same data and different data along with the encryption and decryption of the secret message using public key cryptographic
algorithm, makes data more secure and transparency is minimized. In this paper a data hiding technique is proposed for high
resolution video. The intension is to provide proper protection on data during transmission. For the accuracy of the correct
message output that extract from source tools for comparison can be used and statistical analysis can be done. Its main
advantage is that it is a blind scheme and its affect on video quality or coding efficiency is almost negligible. It is highly
configurable, thus it may result in high data capacities. Finally, it can be easily extended, resulting in better robustness, better
data security and higher embedding capacity.
ACKNOWLEDGEMENT
The authors are very much thankful to Prof. Shalabh Agarwal, Head, Department of Computer Science for giving
permission to do research work in the field of Steganography. One of the authors AN is also grateful to Fr. Dr. J. Felix Raj for
giving all time inspiration to do research work in Computer Science and Engineering.
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4. Asoke Nath, Sankar Das, Amlan Chakraborti, “Data Hiding and Retrieval” published in IEEE “Proceedings of International Conference on Computational Intelligence and Communication Networks (CICN 2010)” held from 26-28 NOV’2010 at Bhupal, Page: 392-397(2010).
5. Joyshree Nath, Sankar Das, Shalabh Agarwal and Asoke Nath, “Advanced steganographic approach for hiding encrypted secret message in LSB, LSB+1, LSB+2 and LSB+3 bits in non standard cover files”, International Journal of Computer Applications, Vol14-No.7,Page-31-35, Feb(2011).
6. Joyshree Nath, Sankar Das, Shalabh Agarwal and Asoke Nath, “ Advanced Steganography Algorithm using encrypted secret message”, International Journal of Advanced Computer Science and Applications, Vol-2, No-3, Page-19-24, March(2011).
7. Joyshree Nath, Sankar Das, Shalabh Agarwal and Asoke Nath, “A Challenge in hiding encrypted message in LSB and LSB+1 bit positions in any cover files : executable files, Microsoft office files and database files, image files, audio files and video files “,JGRCS, Vol- 2,No.4,Page:180-185,April (2011)
8. Agniswar Dutta, Abhirup Kumar Sen, Sankar Das, Sankar das, Shalabh Agarwal and Asoke Nath, “New Data Hiding Algorithm in MATLAB using Encrypted secret message”, Proceedings of IEEE CSNT-2011 held at SMVDU(Jammu) 03-06 June 2011, Page 262-267(2011).
9. Joyshree Nath, Meheboob Alam Mallik, Saima Ghosh and Asoke Nath, “ An efficient data hiding method using encrypted secret message obtained by MSA algorithm”, Proceedings of the International conference Worldcomp 2011 held at Las Vegas(USA), 18-21 Jul(2011), Page 312-318, Vol-1(2011)
10. Rishav Ray, Jeeyan Sanyal,Tripti Das, Kaushik Goswami, Sankar Das and Asoke Nath , “A new randomized data hiding algorithm with encrypted secret message using modified generalized Vernam Cipher Method: RAN-SEC algorithm, Proceedings of IEEE International conference : World Congress WICT-2011 held at Mumbai University 11-14 Dec, 2011, Page No. 1215-1220 (2011).
11. Rishav Ray, Jeeyan Sanyal, Debanjan Das, Asoke Nath, “A new Challenge of hiding any encrypted secret message inside any Text/ASCII file or in MS word file : RJDA Algorithm”, Proceedings of IEEE CSNT-2012 conference held at Rajkot May 11-13, 2012, Page:889-893(2012).
12. Sayak Guha, Tamodeep Das, Saima Ghosh, Joyshree Nath, Sankar Das, Asoke Nath, “A new data hiding algorithm with encrypted secret message using TTJSA symmetric key crypto system”, Journal of Global Research in Computer Science, Vol 3, No.4, Page-11-16(2012).
13. Joyshree Nath, Saima Ghosh and asoke nath, “Advanced Digital Steganography using Encrypted Secret Message and Encrypted Embedded Cover File”, International Journal of Computer Applications(IJCA 0975-8887), Vol 46, No-14, May ,(2012).
14. Somdip Dey, Kalyan Mondal, Joyshree Nath, Asoke Nath, “Advanced Steganography Algorithm Using Randomized Intermediate QR Host Embedded with Any Encrypted Secret Message : ASA_QR Algorithm”, International Journal of Modern Education and Computer Science, No.6, Page 59-67, 2012.
15. Joyshree Nath, Saima Ghosh, Asoke Nath, “Data hiding algorithm using two-way encryption and embedding in a cover file – A new method for sending password or confidential message”, Proceedings of International Conference Worldcomp 2012 held at Las Vegas, USA, IPCV-12, Page-414 – 420(2012).
16. Somdip Dey, Joyshree Nath, Asoke Nath, “A New Technique to Hide Encrypted Data in QR CodesTM “, Proceedings of International Conference Worldcomp 2012 held at Las Vegas, USA, ICOMP-12, Page-94 – 101(2012).
Pritha et al. International Journal of Advance Research in Computer Science and Management Studies Volume 2, Issue 12, December 2014 pg. 46-59
© 2014, IJARCSMS All Rights Reserved ISSN: 2321‐7782 (Online) 59 | P a g e
AUTHOR(S) PROFILE
Pritha Roy is currently pursuing her M.Sc. degree in Computer Science from St. Xavier’s College
(Autonomous), Kolkata, India.
Dr. Asoke Nath is Associate Professor in the Department of Computer Science, St. Xavier’s
College (Autonomous), Kolkata, India. Presently he is involved in research work in the areas like
Cryptography and Network security, Steganography, Visual Cryptography, Green Computing,
MOOCs, e-learning Methodologis, Artificial Neural Networks. He has published more than 116
papers in International Journals and conference proceedings.